A scientometric review of research trends in computer-assisted language learning (1977-2020)

This study sought to examine research trends in computer-assisted language learning (CALL) using a retrospective scientometric approach. Scopus was used to search for relevant publications on the topic and generate a dataset consisting of 3,697 studies published in 11 journals between 1977 and 2020. A document co-citation analysis method was adopted to identify the main research clusters in the dataset. The impact of each publication on the field was measured by using the burst index and the betweenness centrality and the content of influential publications was closely analysed to determine the focus of each cluster and the key themes of the studies in focus. Overall, we identified seven major clusters. We further found that leveraging synchronous computer-mediated communication and negotiated interaction, multimedia, telecollaboration or e-mail exchanges, blogs, digital games, Wikis and podcasts to support language learning was probably beneficial for language learning. Varying degrees of support were found in various studies for each of these technologies. Stronger support was found for synchronous computer-mediated communication and negotiated interaction, multimedia, telecollaboration or e-mail exchanges and digital games and weaker support was found for blogs, Wikis, and podcasts. The limitations the supporting studies listed were also considered inconsequential. On the other hand, while there was strong support for blogs, Wikis and podcasts, some major drawbacks were observed. The findings of the study would be helpful for teachers and instructors who want to decide whether to use technology in the classroom for instructional purposes. Additionally, researchers and graduate students who need to identify a research topic for their thesis or dissertation may find the results of the study useful for them, too.